Abstract
Artificial intelligence (AI) has become one of the fastest-growing technologies in healthcare, fundamentally transforming clinical decision-making, disease diagnosis, treatment planning, and patient management. Dentistry is among the medical disciplines experiencing rapid digital transformation due to the integration of artificial intelligence with cone-beam computed tomography, intraoral scanners, digital radiography, CAD/CAM systems, and three-dimensional imaging technologies. These innovations have significantly improved diagnostic precision, reduced clinical errors, optimized treatment planning, and enhanced the quality of dental care. Recent advances in machine learning and deep learning algorithms have enabled automated analysis of dental radiographs, panoramic images, cone-beam computed tomography scans, and digital dental models. Numerous clinical studies have demonstrated that AI systems achieve diagnostic performance comparable to experienced clinicians in detecting dental caries, periapical lesions, periodontal bone loss, root canal morphology, orthodontic abnormalities, and implant planning. Furthermore, AI-based decision-support systems contribute to personalized treatment strategies by integrating radiographic findings with clinical and demographic information. Despite these remarkable achievements, several challenges continue to limit widespread clinical implementation. These include insufficient external validation of AI algorithms, limited availability of standardized datasets, concerns regarding patient privacy and data security, ethical and legal issues, algorithm transparency, and the necessity of maintaining clinician supervision throughout the diagnostic and therapeutic process. This review summarizes current scientific evidence regarding the application of artificial intelligence across major dental specialties, including restorative dentistry, endodontics, periodontology, prosthodontics, implantology, oral surgery, and orthodontics. Additionally, current limitations, ethical considerations, future technological developments, and opportunities for integrating AI into routine dental practice are discussed. Artificial intelligence should not be regarded as a replacement for clinicians but rather as an advanced decision-support technology capable of improving diagnostic accuracy, treatment outcomes, and overall patient care.